{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day04 基础构图元素：坐标轴篇（上）\n",
    "\n",
    "　　在初步了解了`matplotlib`中有关`Figure`和`Axes`对象的概念后，今天我们来将目光缩放到单个**坐标系**的尺度上来，先来看看下面这张图，对单`Axes`构成的图像（以普通的**散点+折线**图为例）中各种基础元素进行了剖析：\n",
    "\n",
    "<center><img src='imgs/图1.png' width=500></img></center>\n",
    "\n",
    "　　其中<font color='red' style='font-weight:bold;'>红色</font>五角星标记的元素即我们介绍过的画布对象，而今天开始往后三天，我们将分上、中、下3天来介绍有关**坐标轴**（*axis*）的常用知识。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:19.948006Z",
     "iopub.status.busy": "2020-10-15T13:37:19.947010Z",
     "iopub.status.idle": "2020-10-15T13:37:20.502031Z",
     "shell.execute_reply": "2020-10-15T13:37:20.502031Z",
     "shell.execute_reply.started": "2020-10-15T13:37:19.948006Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matplotlib版本： 3.3.2\n"
     ]
    }
   ],
   "source": [
    "import matplotlib;print('matplotlib版本：', matplotlib.__version__)\n",
    "import matplotlib.pyplot as plt # 从matplotlib中导入我们最经常使用的pyplot子模块\n",
    "import pandas as pd # 用于处理外部数据集\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 设定默认字体为SimHei以解决中文显示乱码问题\n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决图像负号'-'不正常显示的问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　今天开始我们将会在学习过程中使用到外部数据集，譬如下面我们读入堪称新版“鸢尾花”数据的企鹅数据集："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:20.503028Z",
     "iopub.status.busy": "2020-10-15T13:37:20.503028Z",
     "iopub.status.idle": "2020-10-15T13:37:20.534944Z",
     "shell.execute_reply": "2020-10-15T13:37:20.534944Z",
     "shell.execute_reply.started": "2020-10-15T13:37:20.503028Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>island</th>\n",
       "      <th>bill_length_mm</th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "      <th>body_mass_g</th>\n",
       "      <th>sex</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.1</td>\n",
       "      <td>18.7</td>\n",
       "      <td>181.0</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>186.0</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>40.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>36.7</td>\n",
       "      <td>19.3</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3450.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.3</td>\n",
       "      <td>20.6</td>\n",
       "      <td>190.0</td>\n",
       "      <td>3650.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
       "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
       "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
       "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
       "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
       "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
       "\n",
       "   body_mass_g     sex  year  \n",
       "0       3750.0    male  2007  \n",
       "1       3800.0  female  2007  \n",
       "2       3250.0  female  2007  \n",
       "4       3450.0  female  2007  \n",
       "5       3650.0    male  2007  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读入数据并删除含有缺失值的行\n",
    "data = pd.read_csv('penguins.csv').dropna()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　首先我们来以`bill_length_mm`列为x轴，`body_mass_g`列为y轴，利用`scatter`方法绘制简单的散点图："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:20.536937Z",
     "iopub.status.busy": "2020-10-15T13:37:20.535941Z",
     "iopub.status.idle": "2020-10-15T13:37:20.741452Z",
     "shell.execute_reply": "2020-10-15T13:37:20.741452Z",
     "shell.execute_reply.started": "2020-10-15T13:37:20.536937Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　接下来我们开始学习`matplotlib`中坐标轴相关设置内容："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **坐标轴标签**\n",
    "\n",
    "　　利用`set_xlabel`和`set_ylabel`方法我们可以分别为x轴与y轴标上标签，其常用参数如下，涉及到文字的更多参数我们在之后的课程中会专挑一期详细介绍：\n",
    "\n",
    "> **xlabel/ylabel**：字符串，分别控制要书写的标签文字<br>\n",
    "> **labelpad**：int型，用于控制坐标轴标签与对应坐标轴之间的距离，单位为像素<br>\n",
    "> **loc**：控制坐标轴标签的对齐位置，对于x轴，有`'left'`、`'center'`和`right`三种选项，对于y轴，有`bottom`、`center`和`top`三种选项<br>\n",
    "> **fontdict**：传入控制字体相关参数的键值对字典，更多参数之后日程中会专门作详细介绍"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:20.743447Z",
     "iopub.status.busy": "2020-10-15T13:37:20.742449Z",
     "iopub.status.idle": "2020-10-15T13:37:20.919974Z",
     "shell.execute_reply": "2020-10-15T13:37:20.919974Z",
     "shell.execute_reply.started": "2020-10-15T13:37:20.743447Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "# 添加x轴标签\n",
    "ax.set_xlabel(xlabel='x轴', labelpad=40, loc='right', \n",
    "              fontdict={\n",
    "                  'fontsize': 32, # 控制字体大小\n",
    "                  'color': 'red' # 控制字体颜色\n",
    "              })\n",
    "\n",
    "# 添加y轴标签\n",
    "ax.set_ylabel(ylabel='y轴', labelpad=0, loc='center', \n",
    "              fontdict={\n",
    "                  'fontsize': 20,\n",
    "                  'color': 'green'\n",
    "              });"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **坐标轴范围设置**\n",
    "\n",
    "　　利用`set_xlim`和`set_ylim`可以用来设置对应坐标轴的最小、最大显示范围："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:20.920972Z",
     "iopub.status.busy": "2020-10-15T13:37:20.920972Z",
     "iopub.status.idle": "2020-10-15T13:37:21.046520Z",
     "shell.execute_reply": "2020-10-15T13:37:21.045523Z",
     "shell.execute_reply.started": "2020-10-15T13:37:20.920972Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "# 调整x轴范围\n",
    "ax.set_xlim(0, 60)\n",
    "\n",
    "# 调整y轴范围\n",
    "ax.set_ylim(0, 7000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **坐标轴映射尺度**\n",
    "\n",
    "　　使用`set_xscale`与`set_yscale`方法来改变对应坐标轴的映射尺度，使用参数`value`来切换不同的映射尺度，默认为`'linear'`即线性映射，其他可选的有`'log'`对数映射等"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-15T13:37:21.047519Z",
     "iopub.status.busy": "2020-10-15T13:37:21.047519Z",
     "iopub.status.idle": "2020-10-15T13:37:21.462744Z",
     "shell.execute_reply": "2020-10-15T13:37:21.461748Z",
     "shell.execute_reply.started": "2020-10-15T13:37:21.047519Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "# 调整y轴为对数化映射\n",
    "ax.set_yscale('log');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后测验：\n",
    "\n",
    "　　虽然只是`matplotlib`有关坐标轴知识内容的**上篇**，但相比你已经get到一些实用的方法了，下面请你以**企鹅数据集**中的`bill_depth_mm`列为x轴，`flipper_length_mm`列为y轴，并绘制散点图，并<u>设置**bill_depth_mm为**x轴名称，**flipper_length_mm**为y轴名称，标签摆放位置等参数自由发挥，并设置x轴范围为**bill_depth_mm**列的最小值到平均值之间，将最终的绘制结果导出为分辨率为2000x2000的`png`文件</u>\n",
    "\n",
    "* 请在今天对应的帖子下回复你的文字代码以及导出图片信息的截图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5),dpi=400)\n",
    "\n",
    "ax.scatter(data['bill_depth_mm'], data['flipper_length_mm'])\n",
    "\n",
    "# 添加x轴标签\n",
    "ax.set_xlabel(xlabel='bill_depth_mm', labelpad=10, loc='left', \n",
    "              fontdict={\n",
    "                  'fontsize': 20, # 控制字体大小\n",
    "                  'color': 'red' # 控制字体颜色\n",
    "              })\n",
    "\n",
    "# 添加y轴标签\n",
    "ax.set_ylabel(ylabel='flipper_length_mm', labelpad=10, loc='center', \n",
    "              fontdict={\n",
    "                  'fontsize': 20,\n",
    "                  'color': 'green'\n",
    "              });\n",
    "\n",
    "# 调整x轴范围\n",
    "x_min=data['bill_depth_mm'].min(0)\n",
    "x_mean=data['bill_depth_mm'].mean(0)\n",
    "ax.set_xlim(x_min, x_mean)\n",
    "\n",
    "fig.savefig('demo.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
